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Abstract The presented development is an intelligent diagnostic system for transformers that studied machine learning techniques to determine the operational status of these transformers. The study of these techniques is initiated by observing the quantities that define the operational behavior of large transformers, aiming to identify anomalies in their operation from data from sensors that equipment it in the functioning environment. This large power transformer has a theoretical service life of above 20 years and a low failure rate. Thus, obtaining failure values, which have their evolution monitored for large transformers, is almost nil. Therefore, a supervised machine training methodology to diagnose these cases is practically unfeasible. The study carried out with several traditional intelligent techniques can verify this. Several supervised methods (Closest Neighbor K-th Neighbor, Support Vector Machine, Radial Base Function, Decision Trees, Random Forest, Neural Network, AdaBoost, Gaussian Naive Bayes, and Quadratic Discriminant Analysis) were studied.

Abstract As high-voltage circuit breakers (HVCBs) are responsible for switching off the load in the event of anomalies, they suffer various wear and tear, both on their main contacts and on the other actuation mechanisms. Not only load maneuvers but also weather conditions can bring factors that contribute to deterioration and, consequently, contribute to failures of this component that is so important for energy supply. Both failures and maintenance shutdowns generate costs for substations, something that could be minimized if there was monitoring of the condition of the HVCBs. This paper shows a methodology to analyze the vibration signal of HVCB in order to identify and quantify contact failures. The proposed methodology is verified through an experimental setup. The results show that it is possible not only to identify the fault but also to assess its intensity using vibration analysis.

The integration of renewable energy sources is crucial for achieving sustainability and environmental preservation. However, their intermittent nature poses challenges to electrical system stability, requiring robust integration strategies. Microgrids emerge as a flexible solution, but their successful deployment requires meticulous planning and intelligent operation to overcome these challenges. This paper presents the development of a reduced-scale laboratory dedicated to researching both hardware and software solutions for intelligent microgrid management. The laboratory was designed to incorporate key components that are becoming increasingly important in the present microgrid context, including renewable energy generation, storage systems, electrolyzers for hydrogen production, and combined heat and power sources. While some equipment consists of commercial models, the battery bank, converter, and supervisory systems were custom-designed to meet the specific requirements of the laboratory. The laboratory has proven itself as a robust tool for conducting studies on microgrids, effectively incorporating essential components, addressing pertinent system issues, and allowing for several tests on converting control algorithms.

Hepatitis C Virus (HCV) infection is a leading etiology of liver cirrhosis and its associated complications, namely, decompensated cirrhosis. As such, hepatitis C potentially necessitates liver transplantation and may result in death. Recently, HCV treatment has evolved. Current HCV treatment is effective in curing HCV; some of the agents are pan-genotypic. Numerous countries have adopted an initiative to eliminate HCV. Achieving elimination poses many challenges; it requires improved availability and accessibility of pan-genotypic therapy. Barriers exist at the level of the collective healthcare system and at the level of the individual healthcare providers and patients. Therefore, organized national and local efforts are needed. Surmounting these barriers calls for interventions concerning screening, linkage to care, and treatment delivery. Pertinent barriers include inadequate availability of screening, ill-equipped laboratory testing before treatment, and insufficient access to treatment. Interventions should seek to decentralize laboratory testing and treatment provision, increase funding for resources and personnel, and spread awareness. Special consideration should be allocated to at-risk populations, such as intravenous drug users, refugees, and prisoners. Computerized medical filing and telemedicine have the potential to refine HCV management by enhancing detection, availability, accessibility, and cost-effectiveness.

This paper presents the detailed project of a modular educational kit to be used in research and teaching activities in the area of power electronics - with emphasis on applications in medium voltage multilevel converters. The half bridge topology has been chosen for the submodules, as they can be arranged together in a multitude of other topologies. A system composed by a mother board and daughter cards is presented. A DSP control card and a FPGA System-On-Module are inserted in the mother board in order to control the half bridge submodules. The targets of this project are applications in medium voltage - hence, the communication between the submodules and the FPGA/DSP is performed through optical fibers. Also a self power system is presented for the submodules, in order for them to operate at floating potentials. Experimental results have been presented for the most usual topologies of converters, including a Modular Multilevel Converter operating at 2000V.

Abstract The multicriteria decision-making process is still an open problem, especially when the decision criteria are not numerical or fully outlined. Several numerical, intelligent, or hybrid techniques have been developed, creating contributions to this problem's solution. This paper is another step in this direction. Based on the Modified Analytic Hierarchy Process (MAHP), a methodology for diagnosis and performance analysis is presented for the dispatch ranking of generating units in a thermoelectric plant. The problem is complex because it covers a power plant, where 99 generating units may be dispatched, according to 10 possible evaluation criteria, which should be used together. This article also presents details of the implementation of the sensors necessary to add to the supervisory system existing in the Palmeiras de Goias Thermal Power Plant.